US20070168113A1 - Map-aided vision-based lane sensing - Google Patents
Map-aided vision-based lane sensing Download PDFInfo
- Publication number
- US20070168113A1 US20070168113A1 US11/335,248 US33524806A US2007168113A1 US 20070168113 A1 US20070168113 A1 US 20070168113A1 US 33524806 A US33524806 A US 33524806A US 2007168113 A1 US2007168113 A1 US 2007168113A1
- Authority
- US
- United States
- Prior art keywords
- vehicle
- lane
- roadway
- attribute
- lanes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
- Navigation (AREA)
Abstract
Description
- The present disclosure relates generally to vision-based lane sensing, and more particularly, to utilizing map software to assist in vision-based lane sensing.
- Vision-based lane sensing (LS) systems detect roadway lane markings and can utilize this information for lane departure warning (LDW), road departure warning and lane keeping (LK) purposes in addition to other purposes (e.g., road geometry prediction). In general, the LS algorithms utilize information from both right and left lane markings to inform the driver of an inadvertent lane deviation, or to steer or keep the vehicle within the lane using, for example, electric power steering (EPS) or active front steering (AFS).
- In most situations, the LS system utilizes the contrast between the lane marking and the pavement to detect the markings. For example, a bright white lane marking on black tar pavement can be detected by the image processor without too much difficulty. As this contrast deteriorates, so does the lane sensing performance. In this regard, it is more difficult for the image processor to detect yellow lane markings in a gray scaled image (and to a lesser degree color image) because of the lower intensities that they generate. At the same time, there is an abundance of yellow lane markings on roadways in the United States. For example, as shown in
FIG. 1 , freeways have yellow lane markings on the left side of the road. Another example, as shown inFIG. 2 , is that two-way roads have yellow lane markings dividing the road. It would be very helpful to the vision system if it could be cued to the presence of such yellow colored markers so as to allow the vision system to better adjust its filters to recognize such lane markers. This would also result in reduced computational effort because the vision system would use algorithms directed to detecting yellow lane markings. - According to one aspect of the invention, a method is provided for map-aided vision-based lane sensing. The method includes receiving map information corresponding to a current geographic position of a vehicle on a roadway. The map information includes the number of lanes on the roadway. Information about the number of lanes crossed by the vehicle on the roadway is received from a vision system. It is determined which of the lanes on the roadway is currently occupied by the vehicle based on the map information and the number of lanes crossed by the vehicle on the roadway.
- In another aspect of the invention, a system is provided for map-aided vision-based lane sensing. The system includes an input device for receiving map information corresponding to a current geographic position of a vehicle on a roadway. The map information includes the number of lanes on the roadway. The input device also receives information about the number of lanes crossed by the vehicle on the roadway from the vision system. The system further includes a processor in communication with the input device. The processor includes instructions for facilitating determining which of the lanes on the roadway is currently occupied by the vehicle. The determining is based on the map information and the number of lanes crossed by the vehicle on the roadway.
- In a further aspect of the invention, a computer program product is provided for map-aided vision-based lane sensing. The computer program product includes a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method. The method includes receiving map information corresponding to a current geographic position of a vehicle on a roadway. The map information includes the number of lanes on the roadway. Information about the number of lanes crossed by the vehicle on the roadway is received from the vision system. It is determined which of the lanes on the roadway is currently occupied by the vehicle based on the map information and the number of lanes crossed by the vehicle on the roadway.
- Referring now to the figures, which are meant to be exemplary embodiments, and wherein the like elements are numbered alike:
-
FIG. 1 is a block diagram of a highway with yellow markers on the left road boundary; -
FIG. 2 is a block diagram of yellow markers on a divided roadway; -
FIG. 3 is a block diagram of a system that may be implemented by exemplary embodiments of the present invention; -
FIG. 4 is a process flow that may be implemented by exemplary embodiments of the present invention to determine a lane on a roadway currently occupied by a vehicle; and -
FIG. 5 is a process flow that may be implemented by exemplary embodiments of the present invention to determine an attribute of a lane marker. - To determine whether a lane marker is yellow, exemplary embodiments of the present invention utilize digital road maps, where such road attributes are available and can be provided to the lane sensing (LS) processor in advance. The image processor in the LS processor can utilize this information to adjust the algorithms and/or filters that it utilizes to detect lane markers. For example, the image processor could react by using a proper yellow filter (a typical yellow filter is αR+βG −γB with typical values of α, β>0.5 and γ<0.2) to enhance the detectability of yellow markers, without sacrificing the detectability of white markers. In addition, when the lane marker is white, the computational effort will be reduced by knowing that a lane marker is white.
- On a freeway where the yellow lane marker is on the left side of the road (the leftmost lane), it is useful to know the number of lanes and the lane where the vehicle is traveling. This knowledge provides information about the color of the lane marker useful to the image processor for lane sensing purposes. The combination of global positioning system (GPS) coordinates, map software and a vision system can be utilized to identify the lane where the vehicle is traveling. The number of lanes in the roadway are provided by the map database. As the vehicle enters a road, the vision system can detect the lane markers and keep track of them as the vehicle changes lanes. In this manner, the lane determination software can determine which lane (e.g., lane number) the vehicle is traveling in.
-
FIG. 3 is a block diagram of a system that may be implemented by exemplary embodiments. As depicted inFIG. 3 , avehicle 302 contains alane determination module 308, a vision-basedLS system 310 andmap software 304.FIG. 3 also depicts acamera 312 which serves as an integral part of the vision-basedLS system 310. Themap software 304 may be implemented by any map software known in the art such as NAVTEQ and TeleAtlas. In addition, themap software 304 may be located internally to thevehicle 302 as depicted inFIG. 3 , or alternatively themap software 304 may be located externally to thevehicle 302. Themap software 304 includes a map database with map information. The map database may be stored in the same location as themap software 304 or all and/or portions of the map database may be stored in different geographic location that themaps software 304. Themap software 304 is utilized by exemplary embodiments to provide map information, such as the number of lanes on a roadway, entrance point onto the roadway and roadway type and lane marker type, to thelane determination module 308. Themap software 304 provides this information in response to a GPS coordinate (or other geographic location indicator). - The vision-based
LS system 310 depicted inFIG. 3 may be implemented by any vision-based LS system known in the art such as Mobileye and Iteris. Data from theLS system 310 is utilized by exemplary embodiments to determine which lane in a roadway is currently occupied by thevehicle 302. In exemplary embodiments, the data includes information about how many lanes have been crossed by thevehicle 302 on a roadway and to determine which lane the vehicle is on. In addition, attribute information about the lane markers is transmitted to theLS system 310. TheLS system 310 uses the attribute information to adjust filters and algorithms used by an image processor in theLS system 310 to detect lane markers. - The
GPS 306, depicted inFIG. 3 is an example of a manner of determining a geographic location of thevehicle 302. In exemplary embodiments, theGPS 306 system should be accurate to within about 10 meters (e.g., GPS used by an OnStar system). Any system that provides geographic location data may be utilized in place of theGPS 306. - In exemplary embodiments, the
lane determination module 308 is implemented by software instructions located on a processor (e.g., a microprocessor) within thevehicle 302. In alternate exemplary embodiments, thelane determination module 308 is implemented by hardware and/or software. The input device in thelane determination module 308 may be implemented by any method of receiving information into thelane determination module 308 from themap software 304 and the vision-basedLS system 310. The input device may receive data via a network that is internal and/or external to thevehicle 302. In exemplary embodiments, one or more of the elements depicted inFIG. 3 (e.g., thelane sensing system 310 and the lane determination module 308) are combined into a single module and thus the input device may be a simple read command. -
FIG. 4 is a process flow that may be implemented by exemplary embodiments to determine a lane on a roadway currently occupied by a vehicle. Atblock 402,map software 304 is utilized to determine map information for the roadway, which is the map information corresponding to a current GPS location of the vehicle. The map information is received at thelane determination module 308. In exemplary embodiments themap software 304 requests the GPS location from theGPS device 306 when themap software 304 acquires a request from thelane determination module 308 for map information. In alternate exemplary embodiments, thelane determination module 308 requests the GPS location from theGPS device 306 and then forwards the GPS location to themap software 304. Themap software 304 then returns the map information to thelane determination module 308. - In exemplary embodiments, the information provided by the
map data base 304 includes the number of lanes on the roadway. In alternate exemplary embodiments the map information from themap software 304 also includes a roadway type (e.g., highway, rural road), a lane marker type (e.g., reflector, painted) and/or an entrance point (e.g., left or right side) onto the roadway. In further alternate exemplary embodiments, depending on the information available from themap software 304, the lane marker type is more detailed including, for example, attributes (e.g., color, dotted/solid) of each of the lane markers. - At
block 404, anLS system 310 is utilized to detect the lane markers and to keep track of the number and direction of vehicle lane changes. The information from theLS system 310 is received at thelane determination module 308. - At
block 406, the lane currently occupied by the vehicle is determined. In exemplary embodiments, this is determined based on the data received from theLS system 310 that indicates the number of lanes on the roadway that have been crossed by the vehicle and theirdirections 302. This number is compared to the number of lanes on the roadway. Based on this comparison, the lane currently occupied by thevehicle 302 is determined. Once the lane currently occupied is determined, theLS system 310 may send an update to thelane determination module 308 when thevehicle 302 has changed a lane. Further, theLS system 310 may indicate to thelane determination module 308 whether the change was in the right direction or the left direction. - In exemplary embodiments, the
LS system 310 keeps track of the relative lane number from the point of thevehicle 302 entrance on to the roadway. For example, in a four-lane road, avehicle 302 enters onto the rightmost lane, it crosses two lanes to the left, then one lane to the right, and then crosses two lanes to the left again, and now the vehicle is in the leftmost lane. -
FIG. 5 is a process flow that may be implemented by exemplary embodiments to determine an attribute of a lane marker. Atblock 502, the lane on the roadway currently occupied by thevehicle 302 is determined as discussed above in reference toFIG. 4 . Atblocks vehicle 302 are utilized to assign attributes to lane markers to the left and/or right of thevehicle 302. Atblock 504, if thevehicle 302 is currently occupying the right-most lane of the roadway, the lane marker to the right of the vehicle is set to solid white. Atblock 506, if thevehicle 302 is currently occupying the left-most lane of the roadway, the lane marker to the left of the vehicle is set to solid yellow. - Emphasis has been placed on the left or right lanes, however it should be noted that other lanes of the roadway are always white and mostly dashed (they can also be solid or reflectors). This information can also be used by the vision system processor to enhance robustness.
- At
block 508, the attributes of the lane markers (if known) are transmitted to theLS system 310. TheLS system 310 utilizes the attributes (e.g., color) to select filters for use in detecting the lane markers. If the attribute specifies a color of white, a filter(s) optimized for identifying white lane markers will be utilized by theLS system 310 to detect the lane marker. If the attribute specifies a color of yellow, a filter(s) optimized for detecting yellow lane markers will be utilized by theLS system 310 to detect the lane marker. Alternatively, or in addition, to using different filter types in response to attributes, theLS system 310 may utilize different types of algorithms in response to different attributes. In general, the algorithms required for detecting white lines are less complex than those required for detecting yellow lines. Thus, by knowing attributes about lane markers, such as the color, theLS system 310 may utilize the most efficient algorithms for detecting lane markers. - In addition, the
lane determination module 308 may use the lane currently occupied by thevehicle 302 to identify the lane position relative to the roadway (e.g., rightmost, leftmost, center). The lane position on the roadway is transmitted to theLS system 310. In exemplary embodiments, theLS system 310 utilizes the lane position on the roadway information to determine what type of warning (or message), to transmit to the operator of thevehicle 302. For example, theLS system 310 may provide stronger warnings to a driver of thevehicle 302 if the vehicle is crossing the center line of a divided roadway or driving off of the roadway. TheLS system 310 may issue different kinds of warnings to a driver of thevehicle 302 depending on whether thevehicle 302 is going off the roadway (e.g., thevehicle 302 is in the rightmost lane and crossing the right lane marker) or whether thevehicle 302 is moving into a different lane on the roadway. - Alternate exemplary embodiments support the detection of Bots Dots (special type of reflectors) on a roadway used to mark lanes. Currently, many roadways in southern states (e.g., California, Texas) have Bots Dots as sole lane markers and are without any painted lane markers. The image processing algorithms required to detect Bots Dots, or reflectors in general, are very different than the algorithms used to detect painted lane markings. Currently, the lane sensing image processor typically runs both algorithms simultaneously and has to make a decision as to which algorithm is the appropriate one and should be selected. Again, this requires extra computational burden and, at times, even inaccurate selection of an algorithm. In such driving scenarios, the information about Bots Dots (or reflectors) can be made available as part of the digital map attributes. This information may be provided to the image processor (e.g., as attributes of the lane markers as described above in reference to
FIG. 5 ) which alleviates the required computational burden and results in a faster and more accurate algorithm selection. - Exemplary embodiments of the present invention may be utilized to fuse data from a digital map database with an image processor on a LS system to enhance the robustness of the LS system and to reduce the computational burden of the LS system. The ability to detect road departures as well as lane departures may lead to the enhanced robustness of the LS system. The ability to identify attributes of a lane marker (e.g., color, type) allows the LS system to utilize filters and algorithms that will detect the lane markers in a more efficient manner and reduce computational burden.
- As described above, the embodiments of the invention may be embodied in the form of hardware, software, firmware, or any processes and/or apparatuses for practicing the embodiments. Embodiments of the invention may also be embodied in the form of computer program code containing instructions embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other computer-readable storage medium, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. The present invention can also be embodied in the form of computer program code, for example, whether stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits.
- While the invention has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims. Moreover, the use of the terms first, second, etc. do not denote any order or importance, but rather the terms first, second, etc. are used to distinguish one element from another.
Claims (21)
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/335,248 US8676492B2 (en) | 2006-01-19 | 2006-01-19 | Map-aided vision-based lane sensing |
DE102007002204A DE102007002204A1 (en) | 2006-01-19 | 2007-01-16 | Map-based view-based track detection |
CNA2007100841986A CN101004351A (en) | 2006-01-19 | 2007-01-19 | Map-aided vision-based lane sensing |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/335,248 US8676492B2 (en) | 2006-01-19 | 2006-01-19 | Map-aided vision-based lane sensing |
Publications (2)
Publication Number | Publication Date |
---|---|
US20070168113A1 true US20070168113A1 (en) | 2007-07-19 |
US8676492B2 US8676492B2 (en) | 2014-03-18 |
Family
ID=38264304
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US11/335,248 Active 2030-09-23 US8676492B2 (en) | 2006-01-19 | 2006-01-19 | Map-aided vision-based lane sensing |
Country Status (3)
Country | Link |
---|---|
US (1) | US8676492B2 (en) |
CN (1) | CN101004351A (en) |
DE (1) | DE102007002204A1 (en) |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20080040039A1 (en) * | 2006-05-17 | 2008-02-14 | Denso Corporation | Road environment recognition device and method of recognizing road environment |
US20100266161A1 (en) * | 2007-11-16 | 2010-10-21 | Marcin Michal Kmiecik | Method and apparatus for producing lane information |
WO2010128999A1 (en) | 2009-05-04 | 2010-11-11 | Tele Atlas North America Inc. | Apparatus and Method for Lane Marking Analysis |
US20100299063A1 (en) * | 2009-05-21 | 2010-11-25 | Clarion Co., Ltd. | Current Position Determining Device and Current Position Determining Method |
WO2012034596A1 (en) * | 2010-09-16 | 2012-03-22 | Tomtom Polska Sp.Z.O.O. | Improvements in or relating to automatic detection of the number of lanes into which a road is divided |
US20120150437A1 (en) * | 2010-12-13 | 2012-06-14 | Gm Global Technology Operations Llc. | Systems and Methods for Precise Sub-Lane Vehicle Positioning |
US20120314070A1 (en) * | 2011-06-09 | 2012-12-13 | GM Global Technology Operations LLC | Lane sensing enhancement through object vehicle information for lane centering/keeping |
US20130016218A1 (en) * | 2010-03-25 | 2013-01-17 | Pioneer Corporation | Generation device for vehicle-evocative sound and generation method for vehicle-evocative sound |
US20130093393A1 (en) * | 2010-10-05 | 2013-04-18 | Mitsubishi Electric Corporation | Charging control apparatus |
US9460624B2 (en) | 2014-05-06 | 2016-10-04 | Toyota Motor Engineering & Manufacturing North America, Inc. | Method and apparatus for determining lane identification in a roadway |
EP3337197A1 (en) * | 2016-12-15 | 2018-06-20 | Dura Operating, LLC | Method and system for performing advanced driver assistance system functions using beyond line-of-sight situational awareness |
FR3081414A1 (en) * | 2018-05-24 | 2019-11-29 | Psa Automobiles Sa | METHOD AND DEVICE FOR ASSISTING THE AUTOMATED DRIVING OF A VEHICLE IN THE ABSENCE OF PHYSICAL SEPARATION BETWEEN TRAFFIC LANES. |
US20210389153A1 (en) * | 2018-09-30 | 2021-12-16 | Great Wall Motor Company Limited | Traffic lane line fitting method and system |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102007054509A1 (en) * | 2007-11-15 | 2009-05-20 | Robert Bosch Gmbh | Method for determining a position of a vehicle |
US9702098B1 (en) | 2014-01-13 | 2017-07-11 | Evolutionary Markings, Inc. | Pavement marker modules |
US11125566B2 (en) | 2015-07-16 | 2021-09-21 | Ford Global Technologies, Llc | Method and apparatus for determining a vehicle ego-position |
US9878711B2 (en) | 2015-12-14 | 2018-01-30 | Honda Motor Co., Ltd. | Method and system for lane detection and validation |
US10460600B2 (en) | 2016-01-11 | 2019-10-29 | NetraDyne, Inc. | Driver behavior monitoring |
US11322018B2 (en) | 2016-07-31 | 2022-05-03 | NetraDyne, Inc. | Determining causation of traffic events and encouraging good driving behavior |
WO2019068042A1 (en) | 2017-09-29 | 2019-04-04 | Netradyne Inc. | Multiple exposure event determination |
WO2019075341A1 (en) | 2017-10-12 | 2019-04-18 | Netradyne Inc. | Detection of driving actions that mitigate risk |
US11403816B2 (en) * | 2017-11-30 | 2022-08-02 | Mitsubishi Electric Corporation | Three-dimensional map generation system, three-dimensional map generation method, and computer readable medium |
KR102586331B1 (en) * | 2018-11-19 | 2023-10-06 | 현대자동차 주식회사 | System and method for checking lane keeping performance |
US11117576B2 (en) | 2019-02-04 | 2021-09-14 | Denso Corporation | Vehicle lane trace control system |
Citations (34)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5483453A (en) * | 1992-04-20 | 1996-01-09 | Mazda Motor Corporation | Navigation control system with adaptive characteristics |
US5904725A (en) * | 1995-04-25 | 1999-05-18 | Matsushita Electric Industrial Co., Ltd. | Local positioning apparatus |
US5922036A (en) * | 1996-05-28 | 1999-07-13 | Matsushita Electric Industrial Co., Ltd. | Lane detection sensor and navigation system employing the same |
US6385536B2 (en) * | 2000-04-11 | 2002-05-07 | Kabushikikaisha Equos Research | Navigation apparatus, method for map matching performed in the navigation apparatus, and computer-readable medium storing a program for executing the method |
US6411889B1 (en) * | 2000-09-08 | 2002-06-25 | Mitsubishi Denki Kabushiki Kaisha | Integrated traffic monitoring assistance, and communications system |
US6411901B1 (en) * | 1999-09-22 | 2002-06-25 | Fuji Jukogyo Kabushiki Kaisha | Vehicular active drive assist system |
US20020184236A1 (en) * | 2000-07-18 | 2002-12-05 | Max Donath | Real time high accuracy geospatial database for onboard intelligent vehicle applications |
US20030072471A1 (en) * | 2001-10-17 | 2003-04-17 | Hitachi, Ltd. | Lane recognition system |
US6580986B1 (en) * | 1999-08-02 | 2003-06-17 | Nissan Motor Co., Ltd. | Lane-following system by detection of lane marking |
US6741186B2 (en) * | 2001-05-24 | 2004-05-25 | Phillip N. Ross | Infrared road line detector |
US20040143381A1 (en) * | 2002-11-05 | 2004-07-22 | Uwe Regensburger | Switching a turn signal indicator on or off |
US6768944B2 (en) * | 2002-04-09 | 2004-07-27 | Intelligent Technologies International, Inc. | Method and system for controlling a vehicle |
US20040164851A1 (en) * | 2003-02-24 | 2004-08-26 | Crawshaw Richard D. | Lane tracking system employing redundant image sensing devices |
US6813370B1 (en) * | 1999-09-22 | 2004-11-02 | Fuji Jukogyo Kabushiki Kaisha | Lane marker recognizing apparatus |
US6819779B1 (en) * | 2000-11-22 | 2004-11-16 | Cognex Corporation | Lane detection system and apparatus |
US20040262063A1 (en) * | 2003-06-11 | 2004-12-30 | Kaufmann Timothy W. | Steering system with lane keeping integration |
US20050004753A1 (en) * | 2003-06-19 | 2005-01-06 | Michael Weiland | Method of representing road lanes |
US6850841B1 (en) * | 2003-05-15 | 2005-02-01 | Navtech North American, Llc | Method and system for obtaining lane data |
US20050129279A1 (en) * | 2003-11-07 | 2005-06-16 | Unwin Jonathan J. | Method and apparatus for discriminating the colour of road markings |
US20050149251A1 (en) * | 2000-07-18 | 2005-07-07 | University Of Minnesota | Real time high accuracy geospatial database for onboard intelligent vehicle applications |
US20050174223A1 (en) * | 2004-02-09 | 2005-08-11 | Nissan Motor Co., Ltd. | Driving assistance method and system with haptic notification seat |
US6973380B2 (en) * | 2002-11-26 | 2005-12-06 | Nissan Motor Co., Ltd. | Lane keep control apparatus and method for automotive vehicle |
US20060031008A1 (en) * | 2004-06-07 | 2006-02-09 | Makoto Kimura | On-vehicle navigation apparatus, turnoff road guiding method, driving lane specifying device, and driving lane specifying method |
US7016517B2 (en) * | 2001-06-29 | 2006-03-21 | Nissan Motor Co., Ltd. | Travel road detector |
US7030775B2 (en) * | 2002-09-24 | 2006-04-18 | Fuji Jukogyo Kabushiki Kaisha | Vehicle surroundings monitoring apparatus and traveling control system incorporating the apparatus |
US20060106518A1 (en) * | 2004-11-18 | 2006-05-18 | Gentex Corporation | Image acquisition and processing systems for vehicle equipment control |
US7058494B2 (en) * | 2003-01-31 | 2006-06-06 | Nissan Motor Co., Ltd. | Vehicle dynamics control apparatus |
US7113866B2 (en) * | 2004-06-15 | 2006-09-26 | Daimlerchrysler Ag | Method and device for determining vehicle lane changes using a vehicle heading and a road heading |
US20070021912A1 (en) * | 2005-01-06 | 2007-01-25 | Aisin Aw Co., Ltd. | Current position information management systems, methods, and programs |
US7224290B2 (en) * | 2001-11-30 | 2007-05-29 | Hitachi, Ltd. | Traffic environment recognition method and system for carrying out the same |
US7254482B2 (en) * | 2001-12-28 | 2007-08-07 | Matsushita Electric Industrial Co., Ltd. | Vehicle information recording system |
US7336203B2 (en) * | 2003-09-24 | 2008-02-26 | Border Gateways Inc. | Traffic control system and method for use in international border zones |
US7424364B2 (en) * | 2004-06-02 | 2008-09-09 | Daimler Ag | Method and device for warning a driver of lane departure |
US7555367B2 (en) * | 2004-06-02 | 2009-06-30 | Nissan Motor Co., Ltd. | Adaptive intention estimation method and system |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6577334B1 (en) | 1998-02-18 | 2003-06-10 | Kabushikikaisha Equos Research | Vehicle control |
DE10226481A1 (en) | 2002-06-14 | 2004-01-15 | Bayerische Motoren Werke Ag | Lane change detection system |
CN1707224A (en) | 2004-06-07 | 2005-12-14 | 日产自动车株式会社 | On-vehicle navigation apparatus and turnoff road guiding method and apparatus and method for determining driving lane |
-
2006
- 2006-01-19 US US11/335,248 patent/US8676492B2/en active Active
-
2007
- 2007-01-16 DE DE102007002204A patent/DE102007002204A1/en not_active Withdrawn
- 2007-01-19 CN CNA2007100841986A patent/CN101004351A/en active Pending
Patent Citations (36)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5483453A (en) * | 1992-04-20 | 1996-01-09 | Mazda Motor Corporation | Navigation control system with adaptive characteristics |
US5904725A (en) * | 1995-04-25 | 1999-05-18 | Matsushita Electric Industrial Co., Ltd. | Local positioning apparatus |
US5922036A (en) * | 1996-05-28 | 1999-07-13 | Matsushita Electric Industrial Co., Ltd. | Lane detection sensor and navigation system employing the same |
US6580986B1 (en) * | 1999-08-02 | 2003-06-17 | Nissan Motor Co., Ltd. | Lane-following system by detection of lane marking |
US6813370B1 (en) * | 1999-09-22 | 2004-11-02 | Fuji Jukogyo Kabushiki Kaisha | Lane marker recognizing apparatus |
US6411901B1 (en) * | 1999-09-22 | 2002-06-25 | Fuji Jukogyo Kabushiki Kaisha | Vehicular active drive assist system |
US6385536B2 (en) * | 2000-04-11 | 2002-05-07 | Kabushikikaisha Equos Research | Navigation apparatus, method for map matching performed in the navigation apparatus, and computer-readable medium storing a program for executing the method |
US20020184236A1 (en) * | 2000-07-18 | 2002-12-05 | Max Donath | Real time high accuracy geospatial database for onboard intelligent vehicle applications |
US7072764B2 (en) * | 2000-07-18 | 2006-07-04 | University Of Minnesota | Real time high accuracy geospatial database for onboard intelligent vehicle applications |
US20050149251A1 (en) * | 2000-07-18 | 2005-07-07 | University Of Minnesota | Real time high accuracy geospatial database for onboard intelligent vehicle applications |
US6411889B1 (en) * | 2000-09-08 | 2002-06-25 | Mitsubishi Denki Kabushiki Kaisha | Integrated traffic monitoring assistance, and communications system |
US6819779B1 (en) * | 2000-11-22 | 2004-11-16 | Cognex Corporation | Lane detection system and apparatus |
US6741186B2 (en) * | 2001-05-24 | 2004-05-25 | Phillip N. Ross | Infrared road line detector |
US7016517B2 (en) * | 2001-06-29 | 2006-03-21 | Nissan Motor Co., Ltd. | Travel road detector |
US20030072471A1 (en) * | 2001-10-17 | 2003-04-17 | Hitachi, Ltd. | Lane recognition system |
US7224290B2 (en) * | 2001-11-30 | 2007-05-29 | Hitachi, Ltd. | Traffic environment recognition method and system for carrying out the same |
US7254482B2 (en) * | 2001-12-28 | 2007-08-07 | Matsushita Electric Industrial Co., Ltd. | Vehicle information recording system |
US6768944B2 (en) * | 2002-04-09 | 2004-07-27 | Intelligent Technologies International, Inc. | Method and system for controlling a vehicle |
US7030775B2 (en) * | 2002-09-24 | 2006-04-18 | Fuji Jukogyo Kabushiki Kaisha | Vehicle surroundings monitoring apparatus and traveling control system incorporating the apparatus |
US20040143381A1 (en) * | 2002-11-05 | 2004-07-22 | Uwe Regensburger | Switching a turn signal indicator on or off |
US6973380B2 (en) * | 2002-11-26 | 2005-12-06 | Nissan Motor Co., Ltd. | Lane keep control apparatus and method for automotive vehicle |
US7058494B2 (en) * | 2003-01-31 | 2006-06-06 | Nissan Motor Co., Ltd. | Vehicle dynamics control apparatus |
US20040164851A1 (en) * | 2003-02-24 | 2004-08-26 | Crawshaw Richard D. | Lane tracking system employing redundant image sensing devices |
US6850841B1 (en) * | 2003-05-15 | 2005-02-01 | Navtech North American, Llc | Method and system for obtaining lane data |
US7510038B2 (en) * | 2003-06-11 | 2009-03-31 | Delphi Technologies, Inc. | Steering system with lane keeping integration |
US20040262063A1 (en) * | 2003-06-11 | 2004-12-30 | Kaufmann Timothy W. | Steering system with lane keeping integration |
US20050004753A1 (en) * | 2003-06-19 | 2005-01-06 | Michael Weiland | Method of representing road lanes |
US7336203B2 (en) * | 2003-09-24 | 2008-02-26 | Border Gateways Inc. | Traffic control system and method for use in international border zones |
US20050129279A1 (en) * | 2003-11-07 | 2005-06-16 | Unwin Jonathan J. | Method and apparatus for discriminating the colour of road markings |
US20050174223A1 (en) * | 2004-02-09 | 2005-08-11 | Nissan Motor Co., Ltd. | Driving assistance method and system with haptic notification seat |
US7424364B2 (en) * | 2004-06-02 | 2008-09-09 | Daimler Ag | Method and device for warning a driver of lane departure |
US7555367B2 (en) * | 2004-06-02 | 2009-06-30 | Nissan Motor Co., Ltd. | Adaptive intention estimation method and system |
US20060031008A1 (en) * | 2004-06-07 | 2006-02-09 | Makoto Kimura | On-vehicle navigation apparatus, turnoff road guiding method, driving lane specifying device, and driving lane specifying method |
US7113866B2 (en) * | 2004-06-15 | 2006-09-26 | Daimlerchrysler Ag | Method and device for determining vehicle lane changes using a vehicle heading and a road heading |
US20060106518A1 (en) * | 2004-11-18 | 2006-05-18 | Gentex Corporation | Image acquisition and processing systems for vehicle equipment control |
US20070021912A1 (en) * | 2005-01-06 | 2007-01-25 | Aisin Aw Co., Ltd. | Current position information management systems, methods, and programs |
Cited By (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20080040039A1 (en) * | 2006-05-17 | 2008-02-14 | Denso Corporation | Road environment recognition device and method of recognizing road environment |
US8694236B2 (en) * | 2006-05-17 | 2014-04-08 | Denso Corporation | Road environment recognition device and method of recognizing road environment |
US8422736B2 (en) * | 2007-11-16 | 2013-04-16 | Tomtom Global Content B.V. | Method of and apparatus for producing lane information |
US20100266161A1 (en) * | 2007-11-16 | 2010-10-21 | Marcin Michal Kmiecik | Method and apparatus for producing lane information |
US20120121183A1 (en) * | 2009-05-04 | 2012-05-17 | Maneesha Joshi | Apparatus and Method for Lane Marking Analysis |
WO2010128999A1 (en) | 2009-05-04 | 2010-11-11 | Tele Atlas North America Inc. | Apparatus and Method for Lane Marking Analysis |
EP2427854A4 (en) * | 2009-05-04 | 2015-09-23 | Tomtom North America Inc | Apparatus and method for lane marking analysis |
US8929660B2 (en) * | 2009-05-04 | 2015-01-06 | Tomtom North America, Inc. | Apparatus and method for lane marking analysis |
US20100299063A1 (en) * | 2009-05-21 | 2010-11-25 | Clarion Co., Ltd. | Current Position Determining Device and Current Position Determining Method |
US8473201B2 (en) * | 2009-05-21 | 2013-06-25 | Clarion Co., Ltd. | Current position determining device and current position determining method for correcting estimated position based on detected lane change at road branch |
US9393906B2 (en) * | 2010-03-25 | 2016-07-19 | Pioneer Corporation | Generation device for vehicle-evocative sound and generation method for vehicle-evocative sound |
US20130016218A1 (en) * | 2010-03-25 | 2013-01-17 | Pioneer Corporation | Generation device for vehicle-evocative sound and generation method for vehicle-evocative sound |
WO2012034596A1 (en) * | 2010-09-16 | 2012-03-22 | Tomtom Polska Sp.Z.O.O. | Improvements in or relating to automatic detection of the number of lanes into which a road is divided |
US9355321B2 (en) | 2010-09-16 | 2016-05-31 | TomTom Polska Sp. z o o. | Automatic detection of the number of lanes into which a road is divided |
US20130093393A1 (en) * | 2010-10-05 | 2013-04-18 | Mitsubishi Electric Corporation | Charging control apparatus |
US20120150437A1 (en) * | 2010-12-13 | 2012-06-14 | Gm Global Technology Operations Llc. | Systems and Methods for Precise Sub-Lane Vehicle Positioning |
US8452535B2 (en) * | 2010-12-13 | 2013-05-28 | GM Global Technology Operations LLC | Systems and methods for precise sub-lane vehicle positioning |
US20120314070A1 (en) * | 2011-06-09 | 2012-12-13 | GM Global Technology Operations LLC | Lane sensing enhancement through object vehicle information for lane centering/keeping |
US9460624B2 (en) | 2014-05-06 | 2016-10-04 | Toyota Motor Engineering & Manufacturing North America, Inc. | Method and apparatus for determining lane identification in a roadway |
US10074281B2 (en) | 2014-05-06 | 2018-09-11 | Toyota Motor Engineering & Manufacturing North America, Inc. | Method and apparatus for determining lane identification in a roadway |
EP3337197A1 (en) * | 2016-12-15 | 2018-06-20 | Dura Operating, LLC | Method and system for performing advanced driver assistance system functions using beyond line-of-sight situational awareness |
CN108388240A (en) * | 2016-12-15 | 2018-08-10 | 德韧营运有限责任公司 | The method and system of advanced driving assistance system function is executed using over the horizon context aware |
FR3081414A1 (en) * | 2018-05-24 | 2019-11-29 | Psa Automobiles Sa | METHOD AND DEVICE FOR ASSISTING THE AUTOMATED DRIVING OF A VEHICLE IN THE ABSENCE OF PHYSICAL SEPARATION BETWEEN TRAFFIC LANES. |
US20210389153A1 (en) * | 2018-09-30 | 2021-12-16 | Great Wall Motor Company Limited | Traffic lane line fitting method and system |
Also Published As
Publication number | Publication date |
---|---|
US8676492B2 (en) | 2014-03-18 |
CN101004351A (en) | 2007-07-25 |
DE102007002204A1 (en) | 2007-09-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US8676492B2 (en) | Map-aided vision-based lane sensing | |
CN107346137B (en) | Network-based storage for vehicles and infrastructure data for optimizing vehicle route planning | |
RU2667675C1 (en) | Device for determining position of vehicle and method for determining position of vehicle | |
US7894632B2 (en) | Apparatus and method of estimating center line of intersection | |
US8346473B2 (en) | Lane determining device, lane determining method and navigation apparatus using the same | |
US7463974B2 (en) | Systems, methods, and programs for determining whether a vehicle is on-road or off-road | |
US8160811B2 (en) | Method and system to estimate driving risk based on a hierarchical index of driving | |
US20170182934A1 (en) | Vehicle projection control system and method of controlling image projection | |
JP6734668B2 (en) | Basic map data | |
JPWO2017208296A1 (en) | Object detection method and object detection apparatus | |
US10192438B2 (en) | Electronic apparatus, guide method, and guide system | |
JP2006209511A (en) | Image recognition device and method, position specification device using it, vehicle controller, and navigation device | |
WO2007138854A1 (en) | Vehicle positioning device | |
JP6303564B2 (en) | Position information calibration device, position information calibration application program | |
JP2009133754A (en) | Navigation apparatus, navigation method, and navigation program | |
JP2008039501A (en) | Vehicle navigation apparatus | |
JP2010102575A (en) | Apparatus and method for generating traffic information | |
CN111373223A (en) | Method, device and system for displaying augmented reality navigation information | |
KR100976964B1 (en) | Navigation system and road lane recognition method thereof | |
US20160334238A1 (en) | Navigation apparatus | |
JP2009042167A (en) | Image recognition device and program for image recognition device, as well as navigator and program for navigator therewith | |
JP2015068665A (en) | Map matching device and navigation device including the same | |
CN102201174B (en) | Traveling road estimation system | |
CN112781600A (en) | Vehicle navigation method, device and storage medium | |
JP4953015B2 (en) | Own vehicle position recognition device, own vehicle position recognition program, and navigation device using the same |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LITKOUHI, BAKHTIAR BRIAN;SADEKAR, VARSHA;REEL/FRAME:017419/0020 Effective date: 20060109 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LITKOUHI, BAKHTIAR BRIAN;SADEKAR, VARSHA;REEL/FRAME:018769/0621 Effective date: 20060109 |
|
AS | Assignment |
Owner name: UNITED STATES DEPARTMENT OF THE TREASURY, DISTRICT Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:022201/0448 Effective date: 20081231 Owner name: UNITED STATES DEPARTMENT OF THE TREASURY,DISTRICT Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:022201/0448 Effective date: 20081231 |
|
AS | Assignment |
Owner name: CITICORP USA, INC. AS AGENT FOR BANK PRIORITY SECU Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:022553/0493 Effective date: 20090409 Owner name: CITICORP USA, INC. AS AGENT FOR HEDGE PRIORITY SEC Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:022553/0493 Effective date: 20090409 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:UNITED STATES DEPARTMENT OF THE TREASURY;REEL/FRAME:023124/0519 Effective date: 20090709 Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC.,MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:UNITED STATES DEPARTMENT OF THE TREASURY;REEL/FRAME:023124/0519 Effective date: 20090709 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNORS:CITICORP USA, INC. AS AGENT FOR BANK PRIORITY SECURED PARTIES;CITICORP USA, INC. AS AGENT FOR HEDGE PRIORITY SECURED PARTIES;REEL/FRAME:023127/0402 Effective date: 20090814 Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC.,MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNORS:CITICORP USA, INC. AS AGENT FOR BANK PRIORITY SECURED PARTIES;CITICORP USA, INC. AS AGENT FOR HEDGE PRIORITY SECURED PARTIES;REEL/FRAME:023127/0402 Effective date: 20090814 |
|
AS | Assignment |
Owner name: UNITED STATES DEPARTMENT OF THE TREASURY, DISTRICT Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:023156/0142 Effective date: 20090710 Owner name: UNITED STATES DEPARTMENT OF THE TREASURY,DISTRICT Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:023156/0142 Effective date: 20090710 |
|
AS | Assignment |
Owner name: UAW RETIREE MEDICAL BENEFITS TRUST, MICHIGAN Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:023162/0093 Effective date: 20090710 Owner name: UAW RETIREE MEDICAL BENEFITS TRUST,MICHIGAN Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:023162/0093 Effective date: 20090710 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:UNITED STATES DEPARTMENT OF THE TREASURY;REEL/FRAME:025245/0587 Effective date: 20100420 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS, INC., MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:UAW RETIREE MEDICAL BENEFITS TRUST;REEL/FRAME:025314/0901 Effective date: 20101026 |
|
AS | Assignment |
Owner name: WILMINGTON TRUST COMPANY, DELAWARE Free format text: SECURITY AGREEMENT;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:025327/0041 Effective date: 20101027 |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS LLC, MICHIGAN Free format text: CHANGE OF NAME;ASSIGNOR:GM GLOBAL TECHNOLOGY OPERATIONS, INC.;REEL/FRAME:025781/0001 Effective date: 20101202 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
AS | Assignment |
Owner name: GM GLOBAL TECHNOLOGY OPERATIONS LLC, MICHIGAN Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:WILMINGTON TRUST COMPANY;REEL/FRAME:034184/0001 Effective date: 20141017 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 4TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1551) Year of fee payment: 4 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY Year of fee payment: 8 |